Clothing Category Prediction
Description
This project uses the concept of transfer learning to build a model on top of ResNet-50 to predict the clothing category from an image.
Dataset
I have used the DeepFashion database which is a large-scale fashion database. The dataset can be found here. Note that I have used the "Category and Attribute Prediction Benchmark" from the DeepFashion dataset.
Code Modules and How to run
First the folders inside the "Category and Attribute Prediction Benchmark" need to be downloaded inside the dataset folder.
Next run the create-dataset.py script to split the data into train-val-test data and to prepare the data into an usable format for creating a model. Once the script completes its execution, the data files can be seen inside the split-data folder.
Run the model.ipynb notebook sequentially to train and test the model.
The models subfolder will contain the trained model.